Lessons from America: The role of business improvement districts as an agent of urban regeneration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The government intends to bring out new legislation in 2004 to enable cities to set up Business Improvement Districts (BIDs). These were introduced in Canada in the 1970s but have been most commonly adopted in the USA during the 1980s and 1990s. There are wide variants in terms of scale, budget, role, power and mission, and so BIDs have the advantage of being easily tailored to fit local conditions. In essence they represent a voluntary tax that local businesses impose on themselves, administer themselves and spend themselves. The money is typically spent on combating crime, providing a clean, attractive environment and promoting the local economy of the neighbourhood. BIDs are primarily though not exclusively found in retail areas where businesses have a clear interest in improving the appearance and safety of an area. This paper highlights what can be learned from the American experience of BIDs in terms of scale, scope, strengths, weaknesses and lessons for the implementation of BIDs in the UK. The paper uses secondary research and is the result both of findings derived from American analysis of BIDs and from detailed reading of the websites of a cross section of BIDs across the USA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it